ABSTRACT Detailed characterizations of brain development are essential to understanding factors underlying the emergence of psychopathology and its progression. Corticostriatal thalamocortical (CSTC) circuits are central to current models of both externalizing and internalizing psychopathologies. However, our understanding of their development and the impact of pathologic processes on these circuits is primarily limited to regional structural properties and specific disorders (e.g., Attention Deficit Hyperactivity Disorder). As such, there is a need for a more comprehensive examination of CSTC circuit development and its relations to psychopathology. The overarching goals of the proposed work are to characterize the development of CSTC circuits using structural MRI and resting state functional MRI, and to link variations in their trajectories to the emergence of psychopathology. We will model developmental trajectories of structural morphology and functional interactions within seven CSTC networks defined based on their connectivity with large-scale cortical networks and relate deviations to externalizing and internalizing behaviors. Consistent with recent calls for secondary analysis of existing datasets to accelerate the identification of brain-behavior relationships that may serve as modifiable clinical targets, the proposed work will make use of openly shared pediatric imaging datasets (ages: 5.0-24.0; high resolution T1 anatomical and resting state functional scans for each participant). Specifically, we will generate a large-scale aggregate cross-sectional sample (n = 3918) for the purposes of delineating trajectories for the seven CSTC networks. We train age-prediction models for each of the networks and pool their predictions to generate multivariate CSTC maturity profiles for each individual. These profiles will be used to subtype individuals into neurobiologically homogenous subgroups, which are expected to differ with respect to dimensional measures of psychopathology calculated using the bifactor model framework (i.e. general psychopathology [p-factor], internalizing, externalizing). An aggregate longitudinal sample (n = 250; 3 time- points per participant, each 12-15 months apart) will be generated to evaluate the ability of changes in CSTC maturity profiles over time to predict longitudinal changes in psychopathology. Specific aims of the proposed work are to: 1) Estimate the developmental trajectories of seven CSTC networks; 2) Determine associations between CSTC network maturity profile subtypes and dimensions of psychopathology; and 3) Evaluate predictive relationships between longitudinal changes in maturity profiles and those in dimensions of psychopathology. Given the scale of the datasets employed, cloud-based computing, and optimized analytic frameworks will be leveraged to ensure the feasibility of achieving the proposed work within the project period. All codes developed will be openly shared.